docstr: ivy.Array instance method variant of ivy.corrcoef. This method
  simply wraps the function, and so the docstring for ivy.corrcoef also
  applies to this method with minimal changes.
  
  Parameters
  ----------
  self
      Input array.
  y
      An additional input array.
      `y` has the same shape as `x`.
  rowvar
      If rowvar is True (default), then each row represents a variable, with
      observations in the columns. Otherwise, the relationship is transposed:
      each column represents a variable, while the rows contain observations.
  
  Returns
  -------
  ret
      The corrcoef of the array elements.
  
  Examples
  --------
  >>> a = ivy.array([[0., 1., 2.], [2., 1., 0.]])
  >>> a.corrcoef()
      ivy.array([[ 1., -1.],
                 [-1.,  1.]])
  >>> a.corrcoef(rowvar=False)
      ivy.array([[ 1., nan, -1.],
                 [nan, nan, nan],
                 [-1., nan,  1.]])
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code: def corrcoef(
      self: ivy.Array,
      /,
      *,
      y: Optional[ivy.Array] = None,
      rowvar: bool = True,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """ivy.Array instance method variant of ivy.corrcoef. This method
      simply wraps the function, and so the docstring for ivy.corrcoef also
      applies to this method with minimal changes.
  
      Parameters
      ----------
      self
          Input array.
      y
          An additional input array.
          `y` has the same shape as `x`.
      rowvar
          If rowvar is True (default), then each row represents a variable, with
          observations in the columns. Otherwise, the relationship is transposed:
          each column represents a variable, while the rows contain observations.
  
      Returns
      -------
      ret
          The corrcoef of the array elements.
  
      Examples
      --------
      >>> a = ivy.array([[0., 1., 2.], [2., 1., 0.]])
      >>> a.corrcoef()
          ivy.array([[ 1., -1.],
                     [-1.,  1.]])
      >>> a.corrcoef(rowvar=False)
          ivy.array([[ 1., nan, -1.],
                     [nan, nan, nan],
                     [-1., nan,  1.]])
      """
      return ivy.corrcoef(self._data, y=y, rowvar=rowvar, out=out)
  
file_path: ivy/ivy/data_classes/array/experimental/statistical.py
imports: import abc
  from typing import Optional, Union, Tuple, Sequence
  import ivy
label_desc: Use image node_id 7 for calling the _ArrayWithStatisticalExperimental obj's underlying member method code with example usage: obj.corrcoef() and returns: ivy